Be Water: An Evolutionary Proof for Trend-Following

TL;DR

This study uses an agent-based model to show that trend-following strategies are evolutionarily more viable than mean-reversion in noisy financial markets, with implications for investors and policy.

Contribution

It introduces MAS-Utopia, a large-scale simulation demonstrating the evolutionary dominance of trend-following strategies over mean-reversion.

Findings

Trend-following strategies emerge as dominant in the simulation.

Mean-reversion strategies are structurally fragile in noisy environments.

The system employs an LLM-driven approach to emulate successful trend-following logic.

Abstract

The proliferation of diverse, high-leverage trading instruments in modern financial markets presents a complex, "noisy" environment, leading to a critical question: which trading strategies are evolutionarily viable? To investigate this, we construct a large-scale agent-based model, "MAS-Utopia," comprising 10,000 agents with five distinct archetypes. This society is immersed in five years of high-frequency data under a counterfactual baseline: zero transaction friction and a robust Unconditional Basic Income (UBI) safety net. The simulation reveals a powerful evolutionary convergence. Strategies that attempt to fight the market's current - namely Mean-Reversion ("buy-the-dip") - prove structurally fragile. In contrast, the Trend-Following archetype, which adapts to the market's flow, emerges as the dominant phenotype. Translating this finding, we architect an LLM-driven system that emulates this successful logic. Our findings offer profound implications, echoing the ancient wisdom of "Be Water": for investors, it demonstrates that survival is achieved not by rigid opposition, but by disciplined alignment with the prevailing current; for markets, it critiques tools that encourage contrarian gambling; for society, it underscores the stabilizing power of economic safety nets.